An Anomaly Detection Approach to Determine Optimal Cutting Time in Cheese Formation

A Loddo, D Ghiani, A Perniciano, L Zedda, B Pes… - Information, 2024 - mdpi.com
The production of cheese, a beloved culinary delight worldwide, faces challenges in
maintaining consistent product quality and operational efficiency. One crucial stage in this …

Efficient textile anomaly detection via memory guided distillation network

J Yang, H Wang, Z Song, F Guo, H Yue - Journal of Intelligent …, 2024 - Springer
Textile anomaly detection with high accuracy and fast frame rates are desired in real
industrial scenarios. To this end, we propose an efficient memory guided distillation network …

[HTML][HTML] Understanding cheese ripeness: An artificial intelligence-based approach for hierarchical classification

L Zedda, A Perniciano, A Loddo… - Knowledge-Based Systems, 2024 - Elsevier
Within the contemporary dairy industry, the effective monitoring of cheese ripeness
constitutes a critical yet challenging task. This paper proposes the first public dataset …

Towards Robust Defect Detection in Casting Using Contrastive Learning

E Intxausti, E Zugasti, C Cernuda, AM Leibar… - … Congress on Pattern …, 2023 - Springer
Defect detection plays a vital role in ensuring product quality and safety within industrial
casting processes. In these dynamic environments, the occasional emergence of new …

Causal interaction modeling on ultra-processed food manufacturing

G Menegozzo, D Dall'Alba… - 2020 IEEE 16th …, 2020 - ieeexplore.ieee.org
In recent years computer science theories have been applied to manufacturing improving
products quality, fault detection and process monitoring. However, there is a lack of research …

Hybrid Approach Integrating Deep Learning-Autoencoder with Statistical Process Control Chart for Anomaly Detection: Case study in Injection Molding Process

F Tayalati, I Boukrouh, L Bouhsaien, A Azmani… - IEEE …, 2024 - ieeexplore.ieee.org
Detecting anomalies in the injection molding process remains a challenging task,
demanding significant resources, data, and expertise due to their impact on cost and time …

An uncertainty-aware deep learning framework for defect detection in casting products

M Habibpour, H Gharoun, AR Tajally, A Shamsi… - arXiv preprint arXiv …, 2021 - arxiv.org
Defects are unavoidable in casting production owing to the complexity of the casting
process. While conventional human-visual inspection of casting products is slow and …

Root-cause analysis with interactive decision trees

A Detzner, R Rückschloß… - 2020 24th International …, 2020 - ieeexplore.ieee.org
When manufacturing products fail, root-cause analysis is essential to improve the affected
products and processes. However, finding the relevant influences among numerous …

Ano-SuPs: Multi-size anomaly detection for manufactured products by identifying suspected patches

H Xu, J Du, A Wang - arXiv preprint arXiv:2309.11120, 2023 - arxiv.org
Image-based systems have gained popularity owing to their capacity to provide rich
manufacturing status information, low implementation costs and high acquisition rates …

Explainable anomaly detection for Hot-rolling industrial process

J Jakubowski, P Stanisz, S Bobek… - 2021 IEEE 8th …, 2021 - ieeexplore.ieee.org
Anomaly detection is emerging trend in manufacturing processes and may be considered as
part of the Industry 4.0 revolution. It can serve both as diagnostic tool in predictive …